Multivariate Analysis and Its ApplicationsIMS, 1994 - 472 стор. |
Загальні терміни та фрази
1980 Subject Classifications algorithm AMS 1980 Subject Anderson approximate assumed Bayesian Bentler bivariate change-point chi-squared coefficient components computed covariance matrix covariance structure defined degrees of freedom denote density function Department of Statistics discriminant procedures example exponential exponential family Fang given H₁ Hong Kong hypothesis IMS Lecture Notes independent inequalities inference Jöreskog LBI test Lemma likelihood function linear model MANOVA Math Mathematical maximum likelihood estimator mean vector method Monograph Series 1994 Multivariate Analysis multivariate distributions multivariate normal distribution null observations obtained Olkin optimal orthogonal parameter polychoric Posterior Probability problem projection pursuit PROOF quadratic quantizer quasirandom random effects random variables random vector rank regression models robust sample Section simulation structural equation models subspace symmetric test statistic Theorem theory univariate University values variance vector quantizer Volume 24 Wishart distribution
Популярні уривки
Сторінка 118 - Canada, the Natural Sciences and Engineering Research Council of Canada and the Fonds pour la Formation de Chercheurs et 1'Aide a la Recherche du Quebec.
Сторінка 298 - In its most general form the model assumes that there is a causal structure among a set of latent variables. The latent variables appear as underlying causes of the observed variables. Latent variables can also be treated as caused by observed variables or as intervening variables in a causal chain.
Сторінка 119 - In Statistics and Probability: Essays in Honor of CR Rao, (G. Kallianpur, PR Krishnaiah and JK Ghosh, eds) pp.
Сторінка 70 - KARLIN, S. and Rinott, Y. (1983). Comparison of measures, multivariate majorization, and applications to statistics.
Сторінка 332 - Lemma 2, and by an argument similar to that used in the proof of Lemma 2.
Сторінка 247 - H. Abut, RM Gray, and G. Rebolledo, "Vector Quantization of Speech and Speech-like Waveforms,
Сторінка 20 - An Introduction to Multivariate Statistical Analysis — Second edition, John Wiley & Sons, 1984.
Сторінка 298 - LISREL is a general computer program for estimating the unknown coefficients in a set of linear structural equations. The variables in the equation system may be either directly observed variables or unmeasured latent variables (hypothetical construct variables) which are not observed but related to observed variables. The computer program is based on a general model which is particularly designed to handle models with latent variables, measurement errors and reciprocal causation (simultaneity, interdependence...
Сторінка 298 - I we shall assume that all variables, observed as well as latent, are measured in deviations from their means. The LISREL model can then be defined as follows. Consider random vectors n1 = (nj, Tl2'***'nm...
Посилання на книгу
Fitting Statistical Distributions: The Generalized Lambda Distribution and ... Zaven A. Karian,Edward J. Dudewicz Попередній перегляд недоступний - 2000 |